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Shadow verification–based waterline detection for unmanned surface vehicles deployed in complicated natural environment
Wei YJ(魏阳杰)1; He YQ(何玉庆)2
Department机器人学研究室
Source PublicationInternational Journal of Advanced Robotic Systems
ISSN1729-8806
2018
Volume15Issue:6Pages:1-12
Indexed BySCI ; EI
EI Accession number20190106327215
WOS IDWOS:000454495000001
Contribution Rank2
Funding OrganizationNational Key Research and Development Plan ; Natural Science Foundation of China ; Fundamental Research Funds for the Central Universities ; State Key Laboratory of Synthetical Automation for Process Industries
KeywordUnmanned Surface Vehicles Waterline Detection Shadow Verification Energy Minimization Natural Environment
Abstract

Boundary separation of operational regions would be helpful for unmanned surface vehicles deployed in dynamic outdoor environments. However, the feasibility and accuracy of current obstacle avoidance methods based on conventional optical images are comparatively poor for unmanned surface vehicle applications, with complicated natural illumination as one of the main sources of error. In this article, a new optical waterline detection method is proposed by combining shadow verification and global optimization (energy minimization). The method is then validated using an actual unmanned surface vehicle operating in outdoor environments. First, the basic principles of intrinsic image are introduced and then employed to evaluate the threshold for background segmentation so that the influence of complicated intensity distribution on the original image is reduced. The properties of different types of shadows are compared, and the basic principles of shadow verification are used to classify the different object regions. Subsequently, the intensity contrast between the shadow and non-shadow regions is used to measure the waterline position based on the relationship between the illumination and the shadow formation. Furthermore, the waterline detection problem is transformed into a problem involving the optimization of energy (minimization) described using differential equations. Finally, experiments are conducted with a series of practical images captured by the unmanned surface vehicle. The experimental results demonstrate the feasibility and robustness of the proposed method.

Language英语
WOS SubjectRobotics
WOS KeywordSAR IMAGES ; COASTLINE
WOS Research AreaRobotics
Funding ProjectNational Key Research and Development Plan[2016YFC0101500] ; Natural Science Foundation of China[61473282] ; Fundamental Research Funds for the Central Universities[N161602002] ; State Key Laboratory of Synthetical Automation for Process Industries
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/23938
Collection机器人学研究室
Corresponding AuthorWei YJ(魏阳杰)
Affiliation1.College of Computer Science and Engineering, Northeastern University, Shenyang Liaoning, China
2.Shenyang Institute of Automation, Chinese Academy of Science, Shenyang Liaoning, China
Recommended Citation
GB/T 7714
Wei YJ(魏阳杰),He YQ(何玉庆). Shadow verification–based waterline detection for unmanned surface vehicles deployed in complicated natural environment[J]. International Journal of Advanced Robotic Systems,2018,15(6):1-12.
APA Wei YJ,&He YQ.(2018).Shadow verification–based waterline detection for unmanned surface vehicles deployed in complicated natural environment.International Journal of Advanced Robotic Systems,15(6),1-12.
MLA Wei YJ,et al."Shadow verification–based waterline detection for unmanned surface vehicles deployed in complicated natural environment".International Journal of Advanced Robotic Systems 15.6(2018):1-12.
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